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COMPARISON OF MULTILEVEL MODEL AND ITS STATISTICAL DIAGNOSTICS

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COMPARISON OF MULTILEVEL MODEL AND ITS STATISTICAL DIAGNOSTICS Diagnostics in Statistical Analysis is atmost important because there may be few influential observations which may distort the inference of the problem statement at hand. It is to be noted that all influential observations are not outliers, but some outliers are influential. In this blog, I will point out few standard statistical diagnostics in multilevel data. Multilevel data and its diagnostics Multi-level models are the statistical models of parameters (like in usual linear regression model) that vary at more than one level. It is also referred with many terms, namely, mixed-effect models, random effect model, hierarchical models and many more. In recent times, with the advent of statistical software and computations, multi-level or hierarchical models are widely used for longitudinal repeated measures analysis and in many meta data applications. Multi-level models could also applicable for non-linear case too

APPLICATION OF TIME SERIES ANALYSIS IN FINANCIAL ECONOMICS

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APPLICATION OF TIME SERIES ANALYSIS IN FINANCIAL ECONOMICS Statswork Nov 23  · 6 min read In this blog, I will explain to you a few applications of  Time Series Analysis  in financial economics. But, before that let us understand what exactly a  time series analysis  and  Data Analysis Time Series Analysis A time series is actually a sequence of data points recorded at regular intervals of time (yearly, quarterly, monthly, daily). Time series includes two types: 1. Univariate — involves a single variable 2. Multivariate — involves two or more variables Let me present you with a list of examples of time series: ü Monthly or daily precipitation of a region ü Daily stock prices (opening, closing) over a period of years/days. ü Monthly bike sales over a period of 3 years ü Annual unemployment rate over a period of 10 years Forecasting Time Series Data The main objective of a  Time Series Analysis  is to develop a suitable mo

Chi-square statistics in research for data analysis

Chi-square statistics in research for data analysis In this blog, I will explain to you what is a chi-square test in a more A clear way and how it can be used for data analysis. Chi-Square Test Things don't generally turn out the way in which you expect in statistical insights. There might be a shrouded predisposition in the decisions individuals make or possibly the information are not made equally. We use a unique statistical test called a chi-square test to address the expected vs the unexpected. It is a unique sort of test that manages frequency of data rather than means as in other statistical tests. Chi-square test is often determines whether to retain the null hypothesis or the problem of the study. If you have two categorical variables in your data and you want to test the relationship between the two, then chi-square test serves the purpose. For any data analysis, the important thing is to formulate the research plan (test statistic, significance level). It sh